Manager, GPU Accelerated Data Analytics

Nvidia

Remote

Quick summary

Work type
Remote
Location
Santa Clara, CA · New York, NY
Salary
$224,000–$356,500 / yr
Posted
81 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $174k
This role $290k
$99k most similar roles pay here $384k

This role pays more than 96% of similar roles. Most pay $126,800–$222,162 — the shaded band above. At the midpoint, this role pays about $290k versus about $174k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 563 open roles on FindRole.

Listed pay typically runs $168,000–$264,500 across 556 roles with salary data.

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View all roles at Nvidia

At a glance

TL;DR · Manager, GPU Accelerated Data Analytics

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Join NVIDIA’s Developer Technology Engineering team as a Senior Performance Engineer where you will lead a global team of experts in optimizing complex workloads across cloud and on-premise environments using NVIDIA's cutting-edge CPUs and GPUs. Your day-to-day involves driving innovation by developing new algorithms, collaborating with architects to enhance hardware performance, and mentoring your team to foster technical excellence. You’ll need an MS or PhD in Computer Science or a related field, along with extensive experience in low-level performance optimization, GPU parallel programming (CUDA), C/C++, and CPU/GPU architecture fundamentals. Ideal candidates also have a track record of building high-performing teams and leading impactful initiatives in distributed high-performance data analytics and modern data center technologies.

Skills

CUDA C/C++ Python GPU CPU Docker Kubernetes AWS Azure CI/CD SQL Vector_Databases Prometheus Grafana

What you'll do

  • Drive innovation by researching and developing techniques to optimize complex workloads on NVIDIA's platform.
  • Lead technical decisions and influence architecture roadmap to advance performance of hardware and software platforms.
  • Build and mentor a distributed team of performance engineers for external developer engagements.
  • Advocate for next-generation products addressing evolving needs of the developer community.
  • Collaborate with leadership and cross-functional partners to drive strategic decision-making and initiative implementation.

What we're looking for

  • MS or PhD in Computer Science, Engineering, or related field.
  • 7+ years experience, including 4+ years in technical roles and 3+ in leadership.
  • Hands-on expertise in GPU parallel programming (e.g., CUDA).
  • Deep knowledge of CPU/GPU architecture fundamentals.
  • Proven track record in building high-performing engineering teams.
  • Strong algorithmic skills with experience in low-level optimizations.
  • Excellent communication and project execution abilities.

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